UAV Control Research Articles

Immersion and Invariance-based Sliding Mode Attitude Control of Tilt Tri-rotor UAV in Helicopter Mode

In this paper, we propose an immersion and invariance-based sliding mode controller for a tilt tri-rotor unmanned aerial vehicle subjects to parameter perturbation, unmodeled dynamics, and external disturbances. The control scheme is divided into three parts, including the disturbance observer, the attitude controller, and the control allocation. Firstly, to alleviate the chattering and improve the robustness for attitude control, the observer using immersion and invariance theory is developed to estimate the disturbance. Note that the observer can relax the requirement of disturbance upper bound and guarantee the convergence of the estimation error. Secondly, to improve the dynamic response capability, a sliding mode attitude controller with an adaptive switch function is designed based on the disturbance observer. Thirdly, a hierarchical control allocation algorithm is proposed. The performance improvement is illustrated by comparing with other sliding mode controllers. Simulations and flight experiments are conducted to verify the effectiveness and applicability of the proposed control scheme.

Design of a H∞ Robust Controller for a Small UAV

For Small Unmanned Aerial Vehicles (SUAV), because of its wide flight envelope and its own flight control system has many uncertainties, the aircraft itself is also vulnerable to strong interference such as atmospheric turbulence, so a robust controller is required to meet the specific performance requirements. In this work, a H∞ algorithm, based on a Linear Matrix Inequality (LMI), is used to the design of multivariable flight control system for the longitudinal motion mathematical model of a SUAV in a key laboratory. The simulation result demonstrated that the control system cannot only guarantee the stability of the closed-loop, but also has good robustness for internal and external disturbances.

Front-End of Vehicle-Embedded Speech Recognition for Voice-Driven Multi-UAVs Control

For reliable speech recognition, it is necessary to handle the usage environments. In this study, we target voice-driven multi-unmanned aerial vehicles (UAVs) control. Although many studies have introduced several systems for voice-driven UAV control, most have focused on a general speech recognition architecture to control a single UAV. However, for stable voice-controlled driving, it is essential to handle the environmental conditions of UAVs carefully, including environmental noise that deteriorates recognition accuracy, and the operating scheme, e.g., how to direct a target vehicle among multiple UAVs and switch targets using speech commands. To handle these issues, we propose an efficient vehicle-embedded speech recognition front-end for multi-UAV control via voice. First, we propose a noise reduction approach that considers non-stationary noise in outdoor environments. The proposed method improves the conventional minimum mean squared error (MMSE) approach to handle non-stationary noises, e.g., babble and vehicle noises. In addition, we propose a multi-channel voice trigger method that can control multiple UAVs while efficiently directing and switching the target vehicle via speech commands. We evaluated the proposed methods on speech corpora, and the experimental results demonstrate that the proposed methods outperform the conventional approaches. In trigger word detection experiments, our approach yielded approximately 7%, 12%, and 3% relative improvements over spectral subtraction, adaptive comb filtering, and the conventional MMSE, respectively. In addition, the proposed multi-channel voice trigger approach achieved approximately 51% relative improvement over the conventional approach based on a single trigger word.

A Formation Reconfiguration Algorithm for Multi‐UAVs Based on Distributed Cooperative Coevolutionary with an Adaptive Grouping Strategy

The Formation reconfiguration problem plays a crucial role in the implementation of complex tasks for multiple unmanned aerial vehicles, which attracted increasing attention in the past decade. Taking into consideration the control parameters and time discretization of the multi-UAVs in the 3 Dimensional (3-D) space, the formation reconfiguration problem can be formulated as a large-scale combinatorial optimization problem with complex constraints and tight couplings between variables. The problem results in the reduction in efficiency and effectiveness using classic bio-inspired algorithms. In this paper, a formation reconfiguration method based on cooperative coevolutionary algorithm is proposed along with a new decomposition strategy to improve the optimization capability and prevent premature convergence. In the proposed approach, variables of multi-UAV are divided into several sub-groups based on an adaptive grouping strategy. The proposed strategy groups the variables in order to better deal with the tight coupling among them, taking into account the variables' variance and multi-UAVs characteristics of the formation reconfiguration problem. Therefore, each subgroup can adopt the Self-adaptive differential evolution strategy with neighborhood search (SaNSDE) with the aim to optimize the UAV's control inputs using multithreaded programming. SaNSDE contributes to calculating the results in a fully distributed and paralleled manner. Optimal solution is then obtained through cooperation and coordination with all subcomponents. Simulation results based on extreme scenarios adopted by previous researches demonstrate that the proposed algorithm outperformed the existing approaches including Particle swarm optimization (PSO), Differential evolution (DE), and the cooperative coevolution algorithms with different well-known grouping strategies.

UAV's Precise Trajectory Tracking Control Based on Nonlinear Dynamic Inverse and Quaternions

The precise tracking 3D trajectory that changes dramatically within the boundary of flight performance is the essential capability of the UAV applied to air combat, which requires that flight control law design be adapted to nonlinear characteristics of flight dynamics and solve the singularities problem during the flight. Continuous trajectory control on the basis of nonlinear dynamic inversion (NDI) is studied. The singularities problem is caused by continuous trajectory expressed by flight velocity and flight-path angles. A sudden change of flight-path axis system happens when aircraft flies along a continuous trajectory which results in singularities. A method for amending flight-path axis system is presented to solve the sudden change problem of flight-path axis system. Finally, the combination of the maneuver generator based on quaternions and amending flight-path axis system realize the precise trajectory tracking control without singularities and obtain excellent tracking characteristics.

Control Optimization of Stochastic Systems Based on Adaptive Correction CKF Algorithm

Standard cubature Kalman filter (CKF) algorithm has some disadvantages in stochastic system control, such as low control accuracy and poor robustness. This paper proposes a stochastic system control method based on adaptive correction CKF algorithm. Firstly, a nonlinear time-varying discrete stochastic system model with stochastic disturbances is constructed. The control model is established by using the CKF algorithm, the covariance matrix of standard CKF is optimized by square root filter, the adaptive correction of error covariance matrix is realized by adding memory factor to the filter, and the disturbance factors in nonlinear time-varying discrete stochastic systems are eliminated by multistep feedback predictive control strategy, so as to improve the robustness of the algorithm. Simulation results show that the state estimation accuracy of the proposed adaptive cubature Kalman filter algorithm is better than that of the standard cubature Kalman filter algorithm, and the proposed adaptive correction CKF algorithm has good control accuracy and robustness in the UAV control test.

Robust Multimode Flight Framework Based on Sliding Mode Control for a Rotary UAV

SUMMARYThis work presents a multimode flight framework control scheme for a quadrotor based on the super twisting algorithm. The controller design stages for six flight control modes are presented. The stability proof for each flight mode is carried out by means of Lyapunov functions, while the stability analysis for the complete control scheme, when a transition from one flight mode to another occurs, is demonstrated using the switching nonlinear systems theory. The performance of the proposed framework is shown in a 3D simulation environment considering a forest fire detection task, which takes into account external disturbances.

IoT-enabled autonomous system collaboration for disaster-area management

Timely investigating post-disaster situations to locate survivors and secure hazardous sources is critical, but also very challenging and risky. Despite first responders putting their lives at risk in saving others, human-physical limits cause delays in response time, resulting in fatality and property damage. In this paper, we proposed and implemented a framework intended for creating collaboration between heterogeneous unmanned vehicles and first responders to make search and rescue operations safer and faster. The framework consists of unmanned aerial vehicles &#x0028 UAVs &#x0029 , unmanned ground vehicles &#x0028 UGVs &#x0029 , a cloud-based remote control station &#x0028 RCS &#x0029 . A light-weight message queuing telemetry transport &#x0028 MQTT &#x0029 based communication is adopted for facilitating collaboration between autonomous systems. To effectively work under unfavorable disaster conditions, antenna tracker is developed as a tool to extend network coverage to distant areas, and mobile charging points for the UAVs are also implemented. The proposed framework&#x02BC s performance is evaluated in terms of end-to-end delay and analyzed using architectural analysis and design language &#x0028 AADL &#x0029 . Experimental measurements and simulation results show that the adopted communication protocol performs more efficiently than other conventional communication protocols, and the implemented UAV control mechanisms are functioning properly. Several scenarios are implemented to validate the overall effectiveness of the proposed framework and demonstrate possible use cases.

Adaptive robust servo constraint tracking control for an underactuated quadrotor UAV with mismatched uncertainties

In this research, to achieve the altitude and attitude tracking control of an underactuated quadrotor UAV with mismatched uncertainties, based upon Udwadia–Kalaba theory, a novel adaptive robust tracking control approach is proposed and which will be designed in two steps. First, aiming at the uncertain and underactuated quadrotor UAV, regardless of initial constraint deviation and mismatched uncertainties, a nominal control is constructed through transforming the desired trajectories into corresponding servo constraints; second, for the mismatched uncertainties, we decompose them into two parts, i.e. the matched part and mismatched part, and the mismatched part will “vanish” during the stability analysis of proposed adaptive robust controller. Eventually, with such a decomposition technique, the large mismatched uncertainties can be addressed properly and the burden of controller design will be reduced to a certain degree. In addition, two deterministic robust control performances are also guaranteed by our proposed approach. The simulation results have shown a good robustness and tracking precision of our proposed scheme for quadrotor UAV.

Development of a methodology to model the dynamic properties of UAVS and high-order control systems

When modeling the dynamic properties of an unmanned aerial vehicle (UAV) and an automatic control system (ACS), it is often necessary to take into account factors such as the lack of rigidity of the aircraft structure, the influence of control and destabilizing factors, which leads to an increase in the order of the model under study. The known numerical and analytical methods do not allow us to obtain general solutions for the variable parameters of the high-order system under study, and at the same time provide the required amount of error and computational costs. A method is developed to model the dynamic properties of UAVs and high-order control systems based on the spectral method, the linear approximation by parts of the input control actions and the spectrum of the system's output signal. An example of using the technique to model the dynamic properties of different orders ACS UAVs (from 1 to 10) with different types of inertia is considered. Based on the analysis of errors in the calculation of the transition process, the effectiveness of the method for analyzing high-order systems is shown based on the required computational costs.

Finite-time path following control for small-scale fixed-wing UAVs under wind disturbances

By integrating the finite time control technique and finite-time disturbance observers together, the finite-time three-dimensional path following control problem for small-scale fixed-wing UAVs subject to external wind disturbances is investigated in this paper. The external wind disturbances are estimated through finite-time disturbance observers and the estimates are then incorporated into the finite-time feedback controller such that a composite control scheme is proposed. Under the proposed control scheme, the closed-loop system possesses not only faster convergence rate but also stronger disturbance rejection ability and better robustness, which is the main contribution of the paper. The effectiveness and superiorities of the proposed composite control scheme are demonstrated by numerical simulations.

Effects of Variable Arm Length on UAV Control Systems

Quadrotor is a type of unmanned aerial vehicle that has been widely used in many applications, such as, policing, surveillance, aerial photography and agriculture. Conventionally, the control of quadrotor flight direction is accomplished by varying speeds of rotors or manipulating torques. In this paper, a novel mechanism is proposed. The mechanism uses stepper rotors to control the arm length for changing flight directions, while maintaining rotors’ speed at constant. This can be achieved using a mathematical analysis of relation between quadrotor arm length and moment of bending of various position of rotor. Analysis and simulation results have shown the change in arm length required to produce moment of bending for hovering, roll and pitch motion. Experimental results have shown that the new mechanism is able to carry more payloads which the rotor speed can be utilized fully at 100% while the flight direction is been controlled by changing of the arm length compared to conventional flight control mechanisms.

Globally Asymptotic Stable Attitude Estimation with Application to MEMS Sensors

Aiming at the requirement of attitude information module with high precision, small size and low power consumption for the control of miniature UAV, a practical attitude estimation algorithm based on the micro-electro-mechanical sensor is proposed in this paper, which realizes the accurate estimation of the attitude of the UAV under the condition of low acceleration. A low-cost MEMS gyroscope, accelerometer, and magnetometer are used in the system. The Euler angle is obtained by the state observer method based on Direction Cosine Matrix (DCM) which can be got by fusing the sensor data. Firstly, based on the basic idea of TRIAD algorithm, a method to determine the attitude rotation matrix by accelerometer and magnetometric measurement is proposed. Compared with the traditional method, this method does not have to calculate the inverse of the matrix. Secondly, a state observer is intended to estimate the attitude of the system. The state observer doesn't have to observe the bias of the gyroscope, but still ensures the convergence of the Euler angle. Finally, the simulation based on the actual sampling data of the MEMS sensor shows that the output of the state observer designed in this paper still has high accuracy and good dynamic characteristics under the condition of gyroscope noise and bias.

Learning Stable Robust Adaptive NARMA Controller for UAV and Its Application to Twin Rotor MIMO Systems

This study presents a nonlinear auto-regressive moving average (NARMA) based online learning controller algorithm providing adaptability, robustness and the closed loop system stability. Both the controller and the plant are identified by the proposed NARMA based input–output models of Wiener and Hammerstein types, respectively. In order to design the NARMA controller, not only the plant but also the closed loop system identification data are obtained from the controlled plant during the online supervised learning mode. The overall closed loop model parameters are determined in suitable parameter regions to provide Schur stability. The identification and controller parameters are calculated by minimizing the $$\varepsilon $$ -insensitive error functions. The proposed controller performances are not only tested on two simulated models such as the quadrotor and twin rotor MIMO system (TRMS) models but also applied to the real TRMS with having severe cross-coupling effect between pitch and yaw. The tracking error performances of the proposed controller are observed better compared to the conventional adaptive and proportional–integral–derivative controllers in terms of the mean squared error, integral squared error and integral absolute error. The most noticeable superiority of the developed NARMA controller over its linear counterpart, namely the adaptive auto-regressive moving average (ARMA) controller, is observed on the TRMS such that the NARMA controller shows a good tracking performance not only for the simulated TRMS model but also the real TRMS. On the other hand, it is seen that the adaptive ARMA is incapable of producing feasible control inputs for the real TRMS whereas it works well for the simulated TRMS model.

Comments on “On decentralized adaptive full-order sliding mode control of multiple UAVs”

In this note is shown that the controller proposed in the paper [ISA Trans 71 (2017) 196–205] has the conceptual flaw of not being decentralized as claimed. A corrected control law is then proposed, maintaining most of the characteristics of the original controller while using only the available information for each agent. The stability of this proposed corrected controller is shown using Lyapunov function technique.

Disturbance observer-based control of UAVs with prescribed performance

ABSTRACTThis work proposes a novel robust nonlinear control method for trajectory tracking of a quadrotor unmanned aerial vehicle using the prescribed performance control technique and disturbance observers, in the presence of external disturbances and uncertainties of physical parameters. By exploiting the cascaded structure of the position subsystems and the attitude subsystems, the controller is designed in a backstepping manner, and the dynamic surface technique is adopted to avoid the explosion of the controller complexity. For each axis of the subsystem with uncertainties, the prescribed performance control technique is adopted to ensure a moderate control performance. Then a disturbance observer is constructed to enhance the corresponding controller to achieve a sufficiently small ultimate error. Not only the control performance of the overall control system, but also the behaviour of all the internal error signals are analysed rigorously. Finally, the performance of the proposed controller is confirmed by simulation studies.

Pasif Başkalaşımın Çıkış Varyansı Kısıtlı Kontrolcü İle Yönlendirilen İha Üzerinde Etkileri

This paper presents novel results for UAVs having passive morphing property and guided by output variance constrained controller (i.e. OVC). Effects of forward and backward motions of wing and horizontal tail in aircraft longitudinal axis in prescribed interval on control energy of variance constrained controller satisfying straight level and constant speed flight of UAV are main interest of this conference paper. A known UAV named as ZANKA-I is used and its data is benefitted for related analyses. Firstly, dynamic modeling of fixed-wing UAVs is given and effect of passive morphing on these models is also investigated. Then, effect of passive morphing on control energy of output variance constrained controller for related UAV using 3-D Matlab graph is presented. Comparisons between control energy versus forward and backward motions of wing and horizontal tail are done.

Design of Attitude Loop Controller for Six-Rotor UAV Based on L1 Adaptive Method

As for the non-modeling dynamics of the six-rotor UAV during the modeling process, and the presence of uncertain external interferences such as crosswinds during flight, the L1 adaptive control method is used to design the attitude controller of the six-rotor UAV. The force analysis of the six-rotor UAV is performed first to establish a nonlinear dynamic model, and then the nonlinear factors and coupling terms of the model are considered as time-varying parameters and disturbances. The low-pass filter is introduced based on the traditional model reference adaptive algorithm, and the L1 adaptive attitude controller is designed to effectively suppress the high-frequency interference caused by mechanical vibrations of the aircraft. Finally, simulation results show that the algorithm has good dynamic performance and robustness while ensuring system stability.

Controller for UAV to Oppose Different Kinds of Wind in the Environment

Small UAVs are susceptible to the external disturbance, especially the wind field disturbance in the atmosphere environment. As a result, UAV’s states including attitude, speed, and position are usually unable to track the desired control commands. In this paper, different types of wind fields which easily affect the UAV are summarized; furthermore, the mechanism of their wind fields affecting the UAV is first strictly analyzed. Next, a novel “reject external disturbance” flight mode for UAV is put forward to offset the trajectory deviation caused by side wind, which makes use of the wind speed information obtained by airspeed and ground speed of UAV. In order to implement the “reject external disturbance” flight mode, the Lyapunov stability theory-based variable model reference adaptive control (VMRAC) system is proposed, and it could also deal with the adverse effects of wind shear and turbulence on UAV flight. Finally, simulation results show that the proposed strategy can significantly improve the trajectory following quality of the UAV under wind disturbance.

Prescribed performance dynamic surface control for trajectory tracking of quadrotor UAV with uncertainties and input constraints

To solve the problem of trajectory tracking control for quadrotor UAV with control input saturation, a novel prescribed performance backstepping dynamic surface control scheme is proposed in the presence of the model uncertainties and unknown external disturbances. In this work, the hyperbolic tangent function is introduced to solve the problem of control input saturation, and construct an auxiliary equation to reduce the saturation effect. Furthermore, the method introduces prescribed performance function, and converts the original constrained system into an equivalent unconstrained system through error transformation. Subsequently, dynamic surface technology is introduced to reduce the complexity of the control algorithm. At the same time, the nonlinear extended state observer is designed to estimate the generalised disturbance of the aircraft system. Finally, the Lyapunov function is selected to prove that all signals of the closed-loop system are uniformly ultimately bounded. Taking DJI M100 aircraft as the simulation object, the results show that the designed controller can effectively solve the problem of control input constraints and enable the system to reach the prescribed transient and steady-state tracking performance indexes.